All you need is a good representation: A multi-level and classifier-centric representation for few-shot learning. (arXiv:1911.12476v1 [cs.CV])

The main problems of few-shot learning are how to learn a generalized representation and how to construct discriminant classifiers with few-shot samples. We tackle both issues by learning a multi-level representation with a classifier-centric constraint. We first build the multi-level representation by combining three different levels of information: local, global, and higher-level. The resulting representation…

Metre as a stylometric feature in Latin hexameter poetry. (arXiv:1911.12478v1 [cs.CL])

This paper demonstrates that metre is a privileged indicator of authorial style in classical Latin hexameter poetry. Using only metrical features, pairwise classification experiments are performed between 5 first-century authors (10 comparisons) using four different machine-learning models. The results showed a two-label classification accuracy of at least 95% with samples as small as ten lines…

Product Knowledge Graph Embedding for E-commerce. (arXiv:1911.12481v1 [cs.LG])

In this paper, we propose a new product knowledge graph (PKG) embedding approach for learning the intrinsic product relations as product knowledge for e-commerce. We define the key entities and summarize the pivotal product relations that are critical for general e-commerce applications including marketing, advertisement, search ranking and recommendation. We first provide a comprehensive comparison…

Dual-Attention Graph Convolutional Network. (arXiv:1911.12486v1 [cs.LG])

Graph convolutional networks (GCNs) have shown the powerful ability in text structure representation and effectively facilitate the task of text classification. However, challenges still exist in adapting GCN on learning discriminative features from texts due to the main issue of graph variants incurred by the textual complexity and diversity. In this paper, we propose a…

Mathematical modelling of the interaction between cancer cells and an oncolytic virus: insights into the effects of treatment protocols. (arXiv:1911.12876v1 [q-bio.CB])

Oncolytic virotherapy is an experimental cancer treatment that uses genetically engineered viruses to target and kill cancer cells. One major limitation of this treatment is that virus particles are rapidly cleared by the immune system, preventing them from arriving at the tumour site. To improve virus survival and infectivity modified virus particles with the polymer…

Systematic external evaluation of published population pharmacokinetic models for tacrolimus in adult liver transplant recipients. (arXiv:1911.12909v1 [q-bio.QM])

Background:Diverse tacrolimus population pharmacokinetic models in adult liver transplant recipients have been established to describe the PK characteristics of tacrolimus in the last two decades. However, their extrapolated predictive performance remains unclear.Therefore,in this study,we aimed to evaluate their external predictability and identify their potential influencing factors. Methods:The external predictability of each selected popPK model was…

Bistability in a SIRS model with general nonmonotone and saturated incidence rate. (arXiv:1911.13002v1 [q-bio.PE])

In this paper, we consider a SIRS model with general nonmonotone and saturated incidence rate and perform stability and bifurcation analysis. We show that the system has saddle-node bifurcation and displays bistable behavior. We obtain the critical thresholds that characterize the dynamical behaviors of the model. We find with surprise that the system always admits…

Finite element simulation of the structural integrity of endothelial cell monolayers: a step for tumor cell extravasation. (arXiv:1911.13035v1 [q-bio.TO])

Cell extravasation is a crucial step of the metastatic cascade. In this process, the circulating tumor cells inside the blood vessels adhere to the cell monolayer of the blood vessel wall and passes through it, which allows them to invade different organs and complete metastasis. In this process, it is relevant to understand how the…

High Order Singular Value Decomposition for Plant Biodiversity Estimation. (arXiv:1911.13076v1 [eess.SP])

We propose a new method to estimate plant biodiversity with R{\’e}nyi and Rao indexes through the so called High Order Singular Value Decomposition (HOSVD) of tensors. Starting from NASA multispectral images we evaluate biodiversity and we compare original biodiversity estimates with those realised via the HOSVD compression methods for big data. Our strategy turns out…

Weakly Supervised Cell Instance Segmentation by Propagating from Detection Response. (arXiv:1911.13077v1 [eess.IV])

Cell shape analysis is important in biomedical research. Deep learning methods may perform to segment individual cells if they use sufficient training data that the boundary of each cell is annotated. However, it is very time-consuming for preparing such detailed annotation for many cell culture conditions. In this paper, we propose a weakly supervised method…